An End-to-End Deep Learning Framework for Cyclone Intensity Estimation in North Indian Ocean Region Using Satellite Imagery
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Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s12524-024-01929-8.pdf
Reference30 articles.
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2. Bonfanti, C., Stewart, J., Hall, D., & Govett, M. (2020). Tropical and extratropical cyclone detection using deep learning. Journal of Applied Meteorology and Climatology, 59(12), 1971–1985. https://doi.org/10.1175/JAMC-D-20-0117.1
3. Chandan, Roy Rita, Kovordányi (2012) Tropical cyclone track forecasting techniques ― A review Atmospheric Research 104-10540-69 10.1016/j.atmosres.2011.09.012
4. Chaudhari, S., Dutta, D., Goswami, S., & Middey, A. (2013). Intensity forecast of tropical cyclones over North Indian Ocean using multilayer perceptron model: Skill and performance verification. Natural Hazards, 65, 97–113. https://doi.org/10.1007/s11069-012-0346-7
5. Chen, B.-F., Chen, B., Lin, H.-T., & Elsberry, R. L. (2019). Estimating tropical cyclone intensity by satellite imagery utilizing convolutional neural networks, vol. 34, issue 2, pp. 447–465, 1 Apr 2019. https://doi.org/10.1175/WAF-D-18-0136.1.
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